Prompt
What's the best identity graph for cookieless retargeting and cross-device audience matching in a DSP stack?
Latest observation
The “best” identity graph depends on your data assets and privacy constraints, but for a DSP stack focused on cookieless retargeting and cross-device audience matching, the strongest setup is usually a hybrid identity graph rather than a single source.
Best practical choice: a hybrid identity graph
Use a graph that combines:
-
Deterministic first-party identities
- hashed email
- login IDs
- phone number
- CRM/customer IDs
- authenticated web/app IDs
-
Publisher/partner-authenticated IDs
- UID2
- LiveRamp RampID
- ID5 ID
- NetID / partner-specific IDs, depending on region
-
Probabilistic/device signals only as a fallback
- IP/user-agent/device relationships
- contextual and household modeling
- use sparingly, because privacy and signal loss make this less stable
What usually wins in practice
For retargeting, the best-performing identity is usually:
- your own first-party authenticated graph
- normalized and activated through a resolver that supports multiple IDs
For cross-device reach, the best-performing graph is usually:
- a walled, privacy-compliant graph with strong deterministic links
- especially if it has broad publisher adoption and clean onboarding
Common top options
1. LiveRamp RampID
Best for:
- enterprise-scale onboarding
- cross-channel addressability
- strong identity resolution across many partners
Pros:
- broad ecosystem adoption
- strong deterministic onboarding
- useful for DSP activation and measurement
Cons:
- can be expensive
- dependency on vendor ecosystem
2. UID2
Best for:
- open-web addressability
- email-based identity
- DSP activation where publishers/adtech partners support it
Pros:
- privacy-conscious design
- good for open web
- interoperable in many ad stacks
Cons:
- depends on email-authenticated supply
- not universal
3. ID5
Best for:
- cookieless web identity
- publisher addressability
- probabilistic + deterministic hybrid coverage
Pros:
- strong in EU/open web contexts
- good scalability across publishers
Cons:
- less ideal if your strategy is heavily first-party CRM-driven
Recommendation by use case
If you are a brand with strong CRM / logged-in traffic
Choose:
- your own first-party identity graph
- plus RampID or UID2
- use it as the core activation layer
If you are a DSP / agency buying across the open web
Choose:
- UID2 + RampID + ID5 support
- with your own graph resolver to map among them
If you need the most future-proof stack
Build around:
- first-party deterministic IDs
- universal ID resolution layer
- publisher-supported IDs
- avoid relying on third-party cookies or pure probabilistic matching
What to avoid
- relying on a single cookie-based graph
- overusing probabilistic matching for retargeting
- buying “identity graphs” that don’t show:
- match methodology
- refresh cadence
- consent coverage
- regional compliance
- publisher adoption
Bottom line
If you want one answer:
The best identity graph for cookieless retargeting and cross-device audience matching in a DSP stack is a first-party deterministic graph activated through a hybrid identity layer like RampID or UID2, with ID5 as a complementary open-web option.
If you want, I can also give you:
- a vendor comparison table for RampID vs UID2 vs ID5, or
- a recommended identity architecture for a DSP stack.
Observation history
See 1 earlier observation
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How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (2 observations for this page). Metrics are distributions over observations, not a single static ranking.
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OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.